Apple
AIML - Sr Machine Learning Engineer, Siri Performance and Reliability
Apple, Seattle, Washington, 98127
AIML - Sr Machine Learning Engineer, Siri Performance and Reliability Seattle,Washington,United States Machine Learning and AI The AIML Performance & Reliability team is looking for a Senior Machine Learning engineer with proven record of building scalable statistical systems for business applications in a fast-paced environment to be the lead developer and architect on the Tools team. As a Senior ML engineer on the AIML Performance & Reliability Tools team, you will have significant influence and responsibility in improving Siri performance and user experience by building a trustworthy and explainable anomaly detection system to automatically identify regressions in Siri performance and alert engineering teams with actionable insights for debugging performance issues. You will be responsible for creating the technical vision for a trustworthy anomaly detection platform by understanding the user requirements, shortcomings of existing approaches, and identifying rigorous statistical methodology scalable for automation. If you're interested, you are someone laser focused on iteratively delivering impact to customers with excellent statistical modeling, programming, problem solving and communication skills, and a passion to build data tools for cross functional customers. By building a trustworthy anomaly regression detection platform, your work will directly impact shipping high performant Siri across various platforms including iOS, VisionPro, WatchOS etc. As a Senior ML engineer on the AIML Performance & Reliability Tools team you will have the opportunity to make broad impact across all Apple platforms in close partnership with Engineering feature and product teams, Testing teams and Quality teams. Your work directly improves Siri’s user experience in the hands of billions of Apple consumers. Description We are looking for a Senior ML Engineer who will set the technical vision for Siri’s automated anomaly detection platform for detecting performance and reliability regressions. You are someone who is passionate about shipping quality code and continually improving our anomaly detection systems. You will be responsible for defining, developing and delivering key features for high quality alerting to enable teams to troubleshoot regressions rapidly. You are someone who works extremely well across teams and organizations and demonstrates strong communication and technical leadership skills and the ability to engage with colleagues and leadership to find common ground on solving hard problems. You are someone who shares technical vision to leadership and engineering teams, gathers feature requirements, defines technical roadmaps and executes efficiently. You will be responsible for technically representing the Tools team and communicating progress on key deliverables across the organization from peer groups to senior leadership. As the Senior ML engineer on the team, you will be responsible for owning the technical roadmap for the team, onboarding and mentoring team members, and leading the team to deliver high-impact outcomes. You are someone comfortable executing in a rapidly changing environment with ambiguous requirements to drive impact incrementally. You demonstrate strong problem solving skills and are self-directed with a proven ability to execute. You continually desire learning and demonstrate attention to details and find opportunities to innovate and share knowledge with others. Minimum Qualifications Graduate degree specializing in the areas of Applied Statistics, Machine Learning, Time Series Analysis or related field Master's degree plus at least 6 years of industry experience in statistical machine learning, or PhD degree with at least 3 years industry experience applying statistical modeling for business problems. 3 years experience building systems based on rigorous statistical or ML methodology, such as anomaly detection using time series analysis, at production scale. 3 years coding experience in programming languages such as Python, Java or Scala Proven record of being customer and impact focused, ability to set the technical vision for long term projects and delivering results iteratively Ability to effectively communicate complex concepts and empower others to leverage self service tools for data analysis and deep-dives Innovative problem solving ability with excellent analytical skills and critical thinking Leadership experience, including being a technical lead for complex development projects demonstrating good technical judgement and prioritization skills. Demonstrated ability to work in a complex cross functional environment, ability to influence at all levels, and build strong relationships to deliver impact. Key Qualifications Preferred Qualifications Prior experience building and owning anomaly detection frameworks for business metrics for different engineering stakeholders. Proven record of delivering analytics tools end to end — from identifying customer requirements to quickly building prototypes to building scalable analytics tools to enable customers. Previous experience in improving system performance and troubleshooting performance bottlenecks. Education & Experience Additional Requirements Pay & Benefits At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $166,600 and $296,300, and your base pay will depend on your skills, qualifications, experience, and location.Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.Learn more (https://www.apple.com/careers/us/benefits.html) about Apple Benefits.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) Apple Footer Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (Opens in a new window) . Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) . Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area. Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) . 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